Data Management Tools
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Data Management Tools |
The Data Management toolbox provides a rich and varied collection of tools that are used to develop, manage, and maintain feature classes, datasets, layers, and raster data structures.
The Data Management toolbox consists of groups of tools, they will be explained with an explanation of all the tools as follows:
Raster Toolset:
The raster Toolset in the data management toolbox provides tools to perform raster management and raster processing. These tools allow you to work with raster properties and create and manipulate raster data:
Mosaic Dataset Tools:
Adds raster datasets to a mosaic dataset from many sources, including a file, folder, table, or web service.
Defines which editing operations nonowners have when editing a mosaic dataset in an enterprise geodatabase.
This tool prevents schema-locking issues that can arise when a mosaic dataset is stored in an enterprise geodatabase. The owner of the geodatabase runs this tool to create any side tables and fields that may be needed by the user. The owner must also grant the proper permissions to allow users to insert, update, or delete records.
Performs checks on a mosaic dataset for errors and possible improvements.
Updates the extent of the boundary when adding new raster datasets to a mosaic dataset that extend beyond its previous coverage.
Computes the extent of every raster in a mosaic dataset. This tool is used when you have added or removed raster datasets from a mosaic dataset and want to recompute the footprints.
Inserts the Cached Raster function as the final step in all function chains within a mosaic dataset.
Defines and generates overviews on a mosaic dataset.
Generate or update seamlines for your mosaic dataset. Seamlines are used to sort overlapping imagery and produce a smoother-looking mosaic.
- You can use this tool to do the following:
- Generate seamlines for all items in the mosaic dataset.
- Generate seamlines for items selected using a query or by an area of interest.
- Update existing seamlines if items are added or removed from the mosaic dataset.
Computes the visibility levels of raster datasets in a mosaic dataset based on the spatial resolution.
Makes transitions from one image to an adjoining image appear seamless.
Identifies areas within a mosaic dataset that have changed since a specified point in time. This is used commonly when a mosaic dataset is updated or synchronized, or when derived products, such as cache, need to be updated. This tool will enable you to limit such processes to only the areas that have changed.
Finds the image candidates within in the mosaic dataset that best represents the mosaic area.
Densely overlapped images are necessary in many projects but can cause uncertainty on which images within the mosaic dataset should be used in your analysis. This tool can help decide which images are optimal, based on areas of maximum overlap and maximum amount of area excluded.
The input mosaic dataset will include a new field named Candidate in the mosaic dataset footprint table. This field determines which images are used in certain operations, such as color balancing, seamline generation, ortho mapping, and mosaic methods.
Creates an empty mosaic dataset in a geodatabase.
Creates a new mosaic dataset from an existing raster catalog, a selection set from a raster catalog, or a mosaic dataset.
Specifies one or more values to be represented as NoData.
Lets you set how mosaic dataset overviews are generated. The settings made with this tool are used by the Build Overviews tool.
Deletes a mosaic dataset, its overviews, and its item cache from disk.
Adds, replaces, or removes a function chain in a mosaic dataset or a raster layer that contains a raster function.
Creates a feature class showing the footprints, boundary, seamlines or spatial resolutions of a mosaic dataset.
Saves a copy of processed images within a mosaic dataset to a specified folder and raster file format.
- There are two common workflows that use this tool:
- Export each processed item of a mosaic dataset to a new file. This allows you to have each processed item as its own stand-alone file. Make sure that you set the appropriate NoData value for the exported items so there are no black borders.
- Export each image within a time series mosaic dataset, based on an area of interest. This allows you to have only the area of interest from each of the time slices.
Creates a table of the file path for each item in a mosaic dataset. You can specify whether the table contains all the file paths or just the ones that are broken.
Masks pixels based on their color or by clipping a range of values. The output of this tool is used as an input to the Color Balance Mosaic Dataset tool to eliminate areas such as clouds and water that can skew the statistics used to color balance multiple images.
Performs batch analysis or processing on image collections contained in a mosaic dataset. The images in the input mosaic dataset can be processed individually or as groups.
The rules of processing can be defined through the Collection Builder parameter and raster function parameters. It generates a new mosaic dataset of processed images. You can optionally choose to save the processed images to disk as separate files. The default condition is to append the input raster function to the mosaic dataset's existing images' function chain, and add it to the output mosaic dataset.
Modifies the geometry for the footprints, boundary, or seamlines in a mosaic dataset to match those in a feature class.
Groups multiple items in a mosaic dataset together as one item.
Removes selected raster datasets from a mosaic dataset.
Resets paths to source imagery if you have moved or copied a mosaic dataset.
Defines the defaults for displaying a mosaic dataset and serving it as an image service.
Splits mosaic dataset items that were merged together using Merge Mosaic Dataset Items.
Keeps your mosaic dataset up to date. In addition to syncing data, you can update overviews if the underlying imagery has been changed, generate new overviews and cache, and restore the original configuration of mosaic dataset items. You can also remove paths to source data with this tool. To repair paths, you need to use the Repair Mosaic Dataset Paths tool.
Synchronization is a one-way operation: changes in the source data can be synchronized to the mosaic dataset’s attribute table, thereby updating the mosaic dataset's attribute table. Changes in the mosaic dataset's attribute table will not affect the source data.
Changes made with the synchronization cannot be undone. You may want to create a backup copy if you've made modifications to your mosaic data that could be overwritten.
Ortho Mapping Tools:
Analyzes the control point coverage and identifies the areas that need additional control points to improve the block adjust result.
- The tool will check each image and provide the following:
- The number of control points for each image
- The percentage of image covered by the control points (point distribution)
- The overlap areas
- The number of control points within overlap areas
Combines control points to an existing control point table.
The points to be appended are the results from either the Compute Tie Points tool or the Compute Control Points tool, or a point feature class.
Applies the geographic adjustments to the mosaic dataset items. This tool uses the solution table from the Compute Block Adjustments tool.
This tool can also reset the geographic adjustments back to the original location.
Builds a stereo model of a mosaic dataset based on a user-provided stereo pair.
A stereo model of a mosaic dataset is required for stereo feature collection and 3D point cloud generation. A stereo model, as one of the tables within a mosaic dataset, defines the stereo pairs. The stereo model stores the overlapping polygons, the corresponding image identifiers, and image IDs that comprise each pair. The stereo model can be accessed from the context menu of a mosaic dataset.
This tool is used to compute the adjustments to the mosaic dataset. This tool will create a solution table that can be used to apply the actual adjustments.
Estimates the exterior camera model and interior camera model from the EXIF header of the raw image and refines the camera models. The model is then applied to the mosaic dataset with an option to use a tool-generated, high-resolution digital surface model (DSM) to achieve better orthorectification.
This is especially helpful for UAV and UAS images, where the exterior and interior camera models are coarse or undefined.
Creates the control points between the mosaic dataset and the reference image. The control points can then be used in conjunction with tie points to compute the adjustments for the mosaic dataset.
Computes the fiducial coordinates in image and film space for each image in a mosaic dataset.
Fiducials are marks, normally four or eight, in aerial photos used as reference. They are an important factor for determining the image transformation from image to film known as interior orientation. This tool is used to automatically find the image coordinates of the fiducials for each images in a mosaic dataset based on a user-provided fiducial template file. A fiducial template file is a table that has required fields for storing either fiducial pictures or paths to the pictures. For more information about fiducials, see Refine Interior Orientation Using Fiducials.
Computes the tie points between overlapped mosaic dataset items. The tie points can then be used to compute the block adjustments for the mosaic dataset.
Generates a report after performing ortho mapping block adjustment to a mosaic dataset. The report is critical in evaluating the quality and accuracy of the ortho mapping products.
Computes 3D points from stereo pairs and outputs a point cloud as a set of LAS files.
The tiling of the LAS files is based on 1,000 by 1,000 ground spacing. The points in each LAS tile are computed by selecting pairs, based on user-defined criteria, and filter points from the selected pairs. The input of this tool is a mosaic dataset that contains a stereo model. The output of this tool can be used to generate a digital terrain model (DTM) or a digital surface model (DSM).
Interpolates a digital terrain model (DTM) or a digital surface model (DSM) from a point cloud using one of the provided interpolation methods.
Creates matching tie points for a given ground control point and initial tie point in one of the overlapping images.
The ortho mapping block adjustment workflow often involves adding ground control points for a more accurate adjustment. One ground control point is typically associated with a tie point in each overlapping image. When there are many overlapping images for one ground control point, manually creating tie points for each image is labor intensive.
Refines the interior orientation for each image in the mosaic dataset by constructing an affine transformation from a fiducial table.
Raster Catalog Tools:
Makes a copy of a raster catalog, including all of its contents, or a subset of its contents if there is a selection.
Creates an empty raster catalog in a geodatabase.
Deletes raster catalog items, including all its contents, or a subset of its contents if there is a selection.
Creates a table listing the paths to the raster datasets contained in an unmanaged raster catalog or a mosaic dataset. The table can display all the file paths, or just the ones that are broken.
Repairs broken file paths or deletes broken links within an unmanaged raster catalog or a mosaic dataset.
Loads all the raster datasets stored in the same workspace into an existing raster catalog.
Raster Dataset Tools:
Saves a copy of a raster dataset or converts a mosaic dataset into a single raster dataset.
Create a raster dataset of random values with a distribution you can define.
Creates an empty raster dataset.
Downloads the source files from an image service or mosaic dataset.
Generates a raster dataset from an input raster function or function chain.
Merges multiple existing raster datasets into an existing raster dataset.
Merges multiple raster datasets into a new raster dataset.
Mosaics the contents of a raster catalog into a new raster dataset.
Merges all of the raster datasets in a folder into one raster dataset.
Raster Processing Tools:
Cuts out a portion of a raster dataset, mosaic dataset, or image service layer.
Creates a single raster dataset from multiple bands.
Calculates an optimal set of pan sharpened weights for new or custom sensor data.
Incorporates elevation data and image metadata to accurately line up imagery.
Combines a high-resolution panchromatic raster dataset with a lower-resolution multiband raster dataset to create a high-resolution multiband raster dataset for visual analysis.
To learn more about pan sharpening, see Learn about panchromatic sharpening.
Creates a new raster dataset from a selection of an HDF or NITF dataset.
Converts a raster function dataset to a table or feature class. The input raster function should be a raster function designed to output a table or feature class.
Splits a raster dataset into separate files based on the DTED tiling structure.
Change the spatial resolution of your raster dataset and set rules for aggregating or interpolating values across the new pixel sizes.
Divides a raster dataset into smaller pieces, by tiles or features from a polygon.
Raster Properties Tools:
Adds a new color map or replaces an existing color map on a raster dataset.
Builds pyramids for multiple raster datasets.
Calculates statistics for multiple raster datasets.
Builds raster pyramids for your raster dataset.
This tool can also be used to delete pyramids. To delete pyramids, set the Pyramids Levels parameter to 0.
Traverses a folder structure, building pyramids and calculating statistics for all the raster datasets it contains. It can also build pyramids and calculate statistics for all the items in a mosaic dataset.
Create or update a table with information about the classes in your raster datasets. This is used primarily with discrete data.
Calculates statistics for a raster dataset or mosaic dataset.
Statistics are required for your raster and mosaic datasets to perform certain tasks, such as applying a contrast stretch or classifying your data.
Convert Raster Function Template
Converts a raster function template between formats (rft.xml, json, and binary).
Removes the color map associated with a raster dataset.
Removes the raster attribute table associated with a raster dataset.
Creates a world file based on the pixel size and the location of the upper left pixel.
Retrieves the value of a given pixel using its x, y coordinates.
Retrieves information from the metadata and descriptive statistics about a raster dataset.
Sets the data type, statistics, and NoData values on a raster or mosaic dataset.
- The same topic is available in Arabic from here:
In the same way, as described through this site. Watch the video first, then you can search for any tool by writing its name in the search, the language of the video is Arabic, but English subtitles and any language in the world are available. Good luck and God bless you.
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